THE INFLUENCE OF TEACHER CUES ON SELF-DIRECTED LEARNING IN MATH EDUCATION

THE INFLUENCE OF TEACHER CUES ON SELF-DIRECTED LEARNING IN MATH EDUCATION

A. Cabo, R. Klaassen (2019).  THE INFLUENCE OF TEACHER CUES ON SELF-DIRECTED LEARNING IN MATH EDUCATION . 11.

Increasing class sizes forces universities to change their education in ways that allow for independent learning for students. This study looks at a case where blended learning was introduced to alleviate some of the educationally negative consequences of large class sizes. Independent learning requires the students to become more self-regulated while at the same time they need efficient feedback from lecturers to enact these self-regulated learning activities. In this paper, we investigate whether at Delft University of Technology (TU Delft) student perceptions of lecturing behaviour is such as to stimulate student’s independent learning and whether self-regulated learning behaviour results in more active engagement with the learning materials. 

Authors (New): 
Annoesjka Cabo
Renate Klaassen
Pages: 
11
Affiliations: 
Delft University of Technology, Netherlands
Keywords: 
Curriculum Renewal
mathematics
Blended Learning
CDIO Standard 1
CDIO Standard 2
CDIO Standard 3
CDIO standard 4
CDIO Standard 7
CDIO Standard 8
CDIO Standard 9
CDIO Standard 10
CDIO Standard 11
CDIO Standard 12
Year: 
2019-01-01 00:00:00
Reference: 
Azevedo, R. & Aleven, V. (2013), International Handbook of Metacognition and Learning Technologies, Springer International Handbooks of Education 26 , Vol. 28: 
Bennet, S., Lockyer, L., Kennedy G., & Dalgarno B. (2018). Understanding self-regulated learning in open-ended online assignment tasks. In R. Ajawi, J. Hong Meng Tai, D. Boud, and P. Dawson (Ed.), Developing Evaluative Judgement in Higher Education: Assessment for Knowing and Producing Quality Work, Routledge: 
Bonk, C.J. & Graham C.R (2006). The handbook of blended Learning: Global perspectives, local designs, John Wiley & Sons: 
Earl, L. (2003). Assessment as Learning: Using Classroom Assessment to Maximise Student Learning. Thousand Oaks, CA, Corwin Press. Learning, Teaching and Assessment Guide. Retrieved from http://www.ltag.education.tas.gov.au: 
Hofer, S. & Stern, E (2016), Underachievement in physics: When intelligent girls fail, Learning and Individual Differences, vol 51, pp 119 -131. : 
10.1016/j.lindif.2016.08.006
Field, A. (2013). Discovering statistics using SPSS. London UK: Sage Publications.: 
Krzic, M., Wilson, J and Hoffman, D. (2018), Scaffolding Student Learning: Forest Floor Example, Journal of Natural Resources and Life Sciences Education 47(1).: 
10.4195/nse2017.11.0023
Van Laar, S. (2018), Supporting Learners in Control; investigating self-regulated learning in blended learning environments, KU Leuven dissertation. : 
Pat-El, R., Tillema, H., Segers, M., & Vedder, P. (2013), Validation of Assessment for Learning; Questionnaires for teachers and students, British Journal of Educational Psychology (2013), 83, 98– 113. Retrieved from www.wileyonlinelibrary.com, The British Psychological Society: 
Ponnan, R., Abdul Malek, M., & Ambalavanan, B. (2015). Large Class Size and Student– Lecturer Learning Experiences at the Tertiary Level, pp 269 -285. In Siew Fun Tan & Loshinikarasi (Ed.), Assessment for Learning Within and Beyond the Classroom, Taylor’s 8th Teaching and Learning Conference Proceedings, Springer: 
Szeto, E. (2014). A comparison of online/face-to-face students' and instructor's Experiences: Examining blended synchronous learning effects. Procedia - Social and Behavioral Sciences, vol. 116, no. 21, pp. 4350-4254.: 
Go to top
randomness